Research on land‐use evolution and ecosystem services value response in mountainous counties based on the SD‐PLUS model

Abstract Rapid urbanization has caused changes in climate and environment and threatened the ecosystem with multiple risks. The ecosystem services capacity has shown a downward trend accordingly. It is significant to explore the spatio‐temporal evolution of land use and ecosystem services value (ESV) in mountainous counties at small scales, as it coordinates economic growth and ecological protection, and promotes sustainable and high‐quality development. Based on the SD‐PLUS model, the study simulated three scenarios of land‐use change in Qianshan city from 2019 to 2035: high‐growth rate, medium‐growth rate, and low‐growth rate, and studied the impacts of land‐use change on the ESV. Results showed that: (1) Under the three scenarios, the construction land in the study area increased significantly, the forest and water have a decreasing trend, and the scale of gardens partly increased. (2) In the urban built‐up areas, a significant amount of construction land is centrally expanded, whereas, in mountainous regions, construction land exhibits sporadic point expansion. And among the various factors that influence land‐use change, the impact of roads at all levels is the most significant, followed by elevation. (3) The overall ESV shows a downward trend, with the low‐growth rate scenario dropping the least (4.91%). The value distribution changes little at the space scale, and different regions demonstrate different degrees of change. From the perspective of value type, the service values of water conservation and waste treatment are significantly reduced, while that of food production is relatively stable; from the perspective of various lands with their ESV, cultivated land and forest remain stable. The study results can provide technical ideas for the coordinated economic development and ecological protection of mountainous cities and boost the implementation of green development.


| INTRODUC TI ON
Biodiversity and ecosystem services (ESs) not only provide people with necessary living goods and means of production but also have multiple ecological, economic, and social values, which are the material basis for human survival (Myers et al., 2000), and a fundamental guarantee for social stability and sustainable development (Tittensor et al., 2014). The degradation of ecosystem functions and the reduction of biodiversity is one of the major ecological and environmental crises facing the world today (Butchart et al., 2010). The proposal of ESs provides a new perspective and basis for biodiversity conservation (Coates, 2018;Silvis, 2012). ESs refer to the natural environment and utility of the ecosystem through its structure and function to sustain human existence (Peh et al., 2014). These services include regulating services, provisioning services, habitat services, etc (de Groot et al., 2012). Ecosystem services value (ESV) is the quantification of the value of natural resources or ESs from a natural ecological perspective, using ecological and economic research methods (Costanza et al., 1997). Land-use change affects the function and structure of ESs by changing the land cover (Song et al., 2018), resulting in changes in ecosystem types, gradual degradation of ESs, and a decline in biodiversity (Larsen, 2004;Schneider et al., 2020), which leads to changes in ESV (Bryan et al., 2018;Kesgin Atak & Ersoy Tonyaloğlu, 2020). Optimizing the land-use pattern according to ESV changes and comprehensively enhancing ESs are of great significance to ecosystem and biodiversity conservation.
Since China's reform and opening up, the rapid and largescale urbanization has caused drastic changes in land use (Hou & Wen, 2020), which is also an important reason for the changes in terrestrial ecosystems and the loss of biodiversity and ESs (Haines-Young, 2009;Wang et al., 2019). Current research focuses on analyzing the spatio-temporal changes in land use and the response of ESV.
However, the majority put their emphasis on land-use change and ESVs of big cities (Dadashpoor & Panahi, 2021), ecologically sensitive areas, and developed coastal areas . Research on small-scale counties, especially mountain areas, remains inadequate.
Mountain areas are crucial for the survival and sustainability of many human societies (Perrigo et al., 2020;Rahbek et al., 2019). On the one hand, mountains are known as cradles of diversity because they provide habitat and refugia for many species (Payne et al., 2020).
And mountain ecosystems provide a vast array of resources (such as trees, food, clean air, or arable land) that are essential to subsistence activities, both for people living in the mountains and for those living outside the mountains . On the other hand, the mountain areas also undertake the function of ecological conservation to protect mankind from the impact of natural disasters (Crouzat et al., 2015; and support urban development (Martín-López et al., 2019). As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of China's social economy (Yang et al., 2019).
Therefore, refined simulation of land-use changes and quantitative assessment of ESV in mountainous areas at the county scale could help coordinate economic development and ecological protection in the area, as well as improve the efficiency of land use, to assist policymakers in making more scientifically based decisions regarding strategies and promoting regional sustainable development.
Spatial-temporal LULC (land use and land cover) models, which can analyze the complex structure of links and feedback by simulating future land-use trajectories, are useful and easy-to-use tools for figuring out the causes and effects of possible future land-use patterns concerning socio-economic and natural environmental factors (Costanza & Ruth, 1998). Cellular automata (CA) models, as a "bottom-up" spatial representation of dynamic systems, are prevalent approaches for simulating the spatial development of LULC by predicting the state of a cell based on its starting state, neighborhood impacts, and a set of transition rules (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017). An increasing amount of research has detailed the applicability of CA models in urban development studies during the last two decades. Nevertheless, the majority of CA models can only simulate the dynamics of single land use (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017), and they cannot easily address how macroscale regulation, economic development, and population migration influence micro-units (Arowolo & Deng, 2018). Furthermore, in CA models, all cells follow the same transition rules; special cells are not recognized (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017).
Compared with the CA model, the SD (system dynamics) model is a top-down macroscopic simulation of land use (Coyle, 1997).
Using SD model, it is possible to simulate complex interactions between components under multiple "hypothesis" situations and to depict the flow and feedback linkages between distinct characteristics (Costanza & Ruth, 1998;Haghani Sang Lee Joon H Byun et al., 2003). However, the SD model cannot simulate individual behavior (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017), and lacks the ability to manage and analyze geospatial data (Guo et al., 2001).
SD models can more accurately replicate the geographical distribution of land use when paired with CA models (Liang et al., 2018). Researchers have created many land-use simulation models (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017), the most popular of which are Logistic-CA (Nasiri et al., 2019), CA-Markov model (Rahnama, 2021), ANN-CA (Ullah et al., 2019), CLUE-S (Clerici et al., 2019), Fore-SCE (Liang et al., 2020), and FLUS (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017). However, these models are ineffective at identifying the variables influencing LULC, do not allow modeling of different land-use patches, particularly natural land-use types, in a dynamic spatio-temporal way, and cannot obtain landuse change rules at certain time intervals . The recently developed advanced patch-generating land-use simulation (PLUS) model can determine the development potential of each land-use type via the Random Forest (RF) algorithm, allowing for more accurate simulations of changes in the spatial distribution of land use (Liang et al., 2021).
Thus, it is urgently needed to study the response of ESV to land use in small-scale mountain areas. To this end, using Qianshan city in southeast China as an example, the objectives of this study are as follows: (a) to simulate land-use changes under multiple scenarios; (b) to explore the potential causes of land-use evolution; (c) to assess ESV and analyze temporal-spatial ESV changes. In summary, this study, by augmenting previous research on the prediction and modeling of land-use patterns, is hoped to provide scientific support for multi-scale territorial and spatial planning and regional sustainable development.

| Overview of the study area
Qianshan City (30°27′-31°04′N; 116°14′-116°46′E) is located in southwest Anhui (Figure 1), located in the subtropical monsoon climate zone. It has a total area of 1688 km 2 , of which 49.3% is made up of mountains and 9.9% is made up of hills. According to the Qianshan Forestry Bureau, by the end of 2021, the forest covers 940 km 2 of land in Qianshan City, which has a total volume of 4.91 × 10 6 m 3 and is mostly broad-leaved deciduous forests. Qianshan City is rich in plant and animal resources, with 1857 kinds of forest plant resources such as ginkgo, cedar, horsetail pine, etc. There are 127 kinds of wild animals, such as otters and small ling cats, among which there are 26 kinds of rare animals. Since the beginning of the 21st century, urbanization has accelerated in Qianshan, and the area of construction has rapidly expanded. This has led to changes in ecosystem structure such as water pollution, forest degradation, and soil erosion, and has threatened the stability of the ecological environment (Miao et al., 2016). At present, Qianshan has been listed as an extremely important region for ecological protection by the Ministry of Ecology and Environment of the People's Republic of China. However, the ecosystem is still under tremendous pressure.

| Data source and processing
The socio-economic data of Qianshan city used in the study comes

| RE S E ARCH ME THOD
The study contains three sub-models. First, the system dynamics model is used to predict the demand for land-use change under the influence of various social and economic factors. Second, the PLUS model is used to simulate land-use change on land demand under multiple scenarios. At last, the ESV assessment model is used to explore the ESV response toward land-use changes under different scenarios ( Figure 2).

| Model construction
The SD model regards the study area as a relatively independent system. The increase or decrease of the total population affects the change in people's demand for different land types, and the variables selected in the study mainly include the total population, urban population, and population change rate. Urban construction land has expanded rapidly in the process of urbanization. At the same time, the phenomenon of "one family with many houses" is widespread in rural areas, therefore, rural construction land is also increasing.
With the rapid development of the economy, investment in fixed assets has increased year-by-year, and a large amount of funds has been invested in land development such as transportation and commercial services, further promoting the expansion of construction land. On the other hand, the growth of economic strength has also played an important supporting role in the restoration of cultivated land, conservation of forest and water, and other natural resources.
From the perspective of the transformation of various types of land, the expansion of construction land is inhibited to a certain extent.
The indicators selected in the economic aspect mainly include GDP, GDP increase, investment in fixed assets, and so on.
The changes in various types of land use are the results of the SD simulation, mainly including construction land, forest, cultivated land, water, etc. Stimulated by population and economic development, the expansion of construction land will occupy a large amount of cultivated land, forest, and other land with good basic conditions. According to the causality between the elements, a variable set of the SD model has been built up in the study. Moreover, existing literature (Gu et al., 2017;Liu et al., 2020;Tan et al., 2019) and scholars in related fields suggest that the SD model is a certain degree of simplification of reality, and cannot fully depict the real situation of reality, so the scope of the study can only be defined by determining the system boundary. This study's SD model focuses primarily on the alteration of land use in mountainous regions from 2018 to 2035, and its spatial scope is the administrative division boundary of Qianshan City. In addition, this study examines the development of the general situation, as the extreme case is not considered. As described below in the SD model parameter setting, the 2011 extreme value will be omitted, as it is not in line with the general trend in most years. Meanwhile, to simplify the calculation, we suppose that the land-use change is affected only by human activities and ignores natural variation. Considering that the change in construction land

| Model verification
The model is debugged and verified based on the existing data of Qianshan city. The model takes 2010 as the basic year, 2011-2018 as the inspection period, and 1 year as the step length. Four indicators including total population, construction land, cultivated land, and forest are selected on a historical inspection basis. The relative error calculation formula is "Relative Error=|simulated value-historical value|/ historical value×100%" (Liu, Liang, et al., 2017;Liu, Zheng, et al., 2017;Liu et al., 2020). The simulation results are given in Table 1.
According to historical test results, the relative errors of the historical and simulated values of the three main state variables: total population, cultivated land, and forest, are all less than 1%, fully complying with the accuracy requirements of the model; the errors of construction land are all less than 2%, also meeting the model's requirements.
In this regard, historical tests have proved the efficacy of the land-use system dynamics model. The model, therefore, can be used to simulate the land-use situation in Qianshan city from 2019 to 2035.

| PLUS model
The research uses PLUS model to predict spatial land-use changes in different scenarios. Socio-economic data such as roads, population distribution, and night lights, and natural ecological data such When the neighborhood effect of a certain type of land is equal to 0, the "seed" for change is generated on the probability surface of development of each land-use type (the output of LEAS). Influenced by the driving factors and conversion rules, the "seed" can generate new land-use types and grow into new patches formed by a group of cells of the same land-use type, to achieve the purpose of simulating land-use changes (Liang et al., 2021).

| Evaluation of ecosystem services value
According to the existing studies (Paulin et al., 2020;Sun et al., 2018), the research adopts the equivalent factor method to evaluate the  Table 2).

In the equation, ESV represents the ecosystem services value (yuan);
A k represents the area (ha); VC k represents the value coefficient of a certain land-use type (yuan/ha).

| Scenario setting
At present, China's economy is at a "New Normal" stage, and there has been a shift in the growth of the economy from high-speed to medium-to-high-speed (Zhang et al., 2016). Qianshan city was upgraded from a county into a city in 2018, and its economic base is still relatively weak and its economic volume is small, so the development growth rate of Qianshan will remain higher than the regional average for some time in the future. Under the guidance of relevant literature Yu, 2021), combined with the possible future policy directions of Qianshan city, the study selects GDP change rate and population change rate as parameters, and sets three scenarios of high-growth scenario, medium-growth scenario, and low-growth scenario to predict the land-use changes of Qianshan city from 2019 to 2035, thus exploring the response of ESV.
Considering the Five-Year Plan is an important tool for guiding social expectations and has a strong guiding effect on economic and social development in China (Hu, 2013;Wang & Gong, 2021).  Table 3.

| Simulation results
The Vensim PLE is adopted for the simulation of the three scenar-  and management, which destroys grassland vegetation and aggravates soil impoverishment. In addition, the grassland ecosystem is relatively less stable compared with forest and water. From the perspective of demand change diversity, cultivated land and forest have a relatively small difference in their demand, indicating that the cultivated land and forest are the major land types that will be invaded for economic development. In the meantime, the garden land for the planting and breeding industry in mountainous cities is also mainly converted from cultivated land and forest.
As the population grows, the demand for food is constantly increasing. If the grain yield cannot be effectively increased, the increase in food demand brought about by population and economic growth will put huge pressure on the demand for cultivated land.
According to the high-growth rate scenario, the most prominent contradiction is between the supply and demand of cultivated land.
Among the three modes, the low-growth rate scenario maintains avoiding too fast economic and population growth. Thus effectively alleviating the pressure on resources and the environment caused by excessive economic growth, while maintaining a stable rate of development also provides the impetus for social sustainability. This mode is also the green development model that China has been promoting in recent years, a way of economic growth and social development that aims at efficiency, harmony, and sustainability .

| Multi-scenario land-use change simulation
The In the southern area of Qianshan urban area (Figure 7), close to government agencies and central hospitals, several public service facilities such as primary and secondary schools, kindergartens, and parks were built in recent years, indicating that intensive construction activities will be carried out in this area over a certain period.
In the scenarios of high-growth rate and medium-growth rate, both Snow Lake and South Lake in this area are occupied by construction land on a considerable scale, and a relatively large area of cultivated land is converted to construction land. While in the low-growth rate scenario, Snow Lake and South Lake generally maintain their status quo, and the expansion of construction land mainly occurs inside the old city, with little expansion outside.

| Scenario diversity analysis
There are differences in the simulation of the three scenarios. The

| ESV changes in different scenarios
Significant changes in different land types have caused changes in ESV in the study area. It can be seen from Table 5

F I G U R E 9
Contribution of each driving factor to the change in land use ESV declined the least (4.91%) in the low-growth rate scenario.
The results show that an appropriate reduction in the pace of economic development will be conducive to maintaining the stability of ESs.
From the perspective of ESV types, water conservation and waste treatment are reduced the most. The reason might be that a large amount of forest and water is converted into construction land, disappeared due to deforestation, or is used for planting and fishfarming, resulting in a decrease in the ESV. In addition, the food production value maintains a small and stable reduction, which is mainly due to the most stringent farmland protection policy in China. The increase in garden area also provides certain food production value.
However, the study area is located in mountainous areas which have limited food production capacity. In this regard, the future land and space planning should explore the delineation of development and construction changes in Qianshan city of different administrative divisions, reasonably integrate rural settlements, and observe the cultivated land red line to enhance the ESV of cultivated land.
From Table 6, it can be seen that the ESV changes of different

| DISCUSS ION
The simulation results of this study are identical to those of related studies on land-use simulations at different scales in Anhui Province (Hu et al., 2020), Yangtze River Delta Zhang, Zhou, & Song, 2020), where Qianshan is located. In this study, the changes in land use and ESV under three different scenarios demonstrated significant spatial heterogeneity. The study revealing that the expansion trend of construction land is evident, while the size of forest and water is rapidly decreasing. The expansion of built-up areas can squeeze the forest and reduce the supply of ESs from the forest. This can lead to a drop in ESV (Delphin et al., 2016), especially in the areas near built-up areas, which suggests that landuse change is the main cause of the drop in ESV (Jiang et al., 2017).
Subsequently, the spatial simulation results showed that the construction land was expanded on a large scale in the built-up areas, while in other areas it was a decentralized dot-like expansion, and that there was a significant spatial autocorrelation in the transformation of various types of land use, indicating that the change was not random. Large-scale Zhang, Zhou, & Song, 2020) and small-scale (Peng et al., 2022) studies in other parts of China have confirmed this change in land use over time.
In the study, the topographic factors (elevation), followed by population distribution and traffic conditions, had the most impact on land-use conversion in the small-scale range of mountainous areas. This is different from the main demographic and economic effects of land change in China's coastal areas (Du et al., 2014) and the western region (Yang et al., 2022). It is indicating that land-use conversion is primarily the result of human transformation activities based on natural topographic conditions.
Finally, we calculated the future ESVs under various scenarios in the study area, with the ESV changes in forest and water being the most significant from the standpoint of various land-use types. From the perspective of various specific ESVs, the decline in the study area's water conservation capacity is the most apparent. As with other findings, ESV changes were most influenced by land-use patterns in forest and water (Aziz, 2021;Rahman & Szabó, 2021).  competitive relationships between different land-use approaches (Liang et al., 2021).
Land-use change is considered to be the greatest threat to nature, leading to a decline in the abundance, diversity, and health of species and ecosystems globally (Davison et al., 2021). Land-use change can have a direct impact on species through habitat destruction and environmental modification (Bender et al., 1998). The simulation of land use and ESV in small-scale mountainous areas in this study can help to reconcile land-use conflicts and is essential for adjusting regional policies on population, industry, and environmental protection and for reconciling human-land relationships, which is important for the precise implementation of biodiversity conservation strategies (Zhao et al., 2015) and ecosystem management decisions (Fu et al., 2019).
Qianshan city is experiencing rapid urbanization. At this stage, land resources are typically utilized for production and living purposes, such as houses, factories, transportation, and parks. The city's original green land and water are also at risk of being encroached upon. Consequently, optimizing land use structures and protecting forests and water to increase the regional ecosystem service value is a critical work for local governments. On the one hand, the economic development rate should be appropriately slowed down, and the transformation of economic development from "high speed" to "high quality" should be encouraged. On the other hand, through afforestation, land that is unsuitable for construction and breeding can be converted into forest to maintain the stability of forest ecosystems and expand the area of forest, thereby enhancing the capacity of regional ESs. The model constructed in this study simulates land-use changes in various scenarios, visually displaying areas that may be occupied and assisting in delimiting urban construction prohibited areas. The simulation results also indicate that the expansion of construction land is relatively dispersed. Therefore, in the current territorial spatial planning work being conducted by Chinese governments at all levels, we should make full use of the unused land between the construction land, perform well in stock excavation, and to conserve land resources and enhance land-use efficiency.
In this study, the ESV changes under different scenarios are intuitively reflected through scenario simulation using the PLUS model.

| CON CLUS ION
The study takes the Qianshan city in Anhui province as the research object, based on current land use, to predict the changes in demand for land use and spatial response in the study area by the SD-PLUS model. In addition, it also discusses the temporal and spatial evolution of ESV. The main conclusions are as follows: 1. It is predicted that the scale of construction land in Qianshan city by 2035 will reach at least 191 km 2 (in the low-growth rate scenario). And the garden land has increased obviously along with the development of characteristic planting industry, while the scale of forest and water exhibit the most significant decrease.

ACK N OWLED G EM ENTS
The authors appreciate the support provided by the Anhui Province

CO N FLI C T O F I NTE R E S T
The authors declare that there is no conflict of interest regarding the publication of this paper.